During vitality of the cenopopulations of Astragalus gly¬cyphyllys L. and Astragalus falcata Lam. species their invasion, normal and regressive types were determined. As well as age spectrum of individuals were defined and it was determined that generative individuals has dominance with their quantity. Vitality of individuals is one of the main features of cenopopulation with the studying of age spectrum of plants. Taking into consideration the role of studied species in increasing of fodder source, organising of drug stock, using them at different areas of industry and other properties studying of these species in cenopopulation level has a great scientific- practical importance.
This study aimed to identify a number of factors involved in hair loss by improving hair growth using a complex extract containing a green tea leaf extract and others (Camellia sinensis & Panax ginseng, CSPG extract). To do so, a C57BL/6J hair-loss mouse model was used and the antioxidant effect of the CSPG extract, the growth of hair, and the manifestation of VEGF proteins in the dermal tissues of mice were measured. Experimental animals were divided into 5 groups (6 per group). Group I was the normal control group. Group II was a vehicle group (hair-loss induced group), and the hair on the back of the mice in this group was removed and moistened with water. Group III was an apply-treat group (0.1g/ml), and the hair on the back was removed and applied with a high-concentration CSPG extract. Group IV was an apply-treat group (0.025g.ml), and the hair on the back was removed and applied with a low-concentration CSPG extract. The last one was the positive control group, and those in this group were treated with ReEn for Alopecia Prevention, a Korean medicinal shampoo for hair loss control that is currently on the market. The antioxidant effect of the CSPG extract was analyzed, and there was no statistical significance between the inhibitory activity of xanthine oxidase, the DPPH (Diphenylpicryl hydrazyl) radical, and the growth of hair. However, the length of hair in the group treated with the high-concentration CSPG extract was longest. The VEGF analysis showed statistically significant results as follows: The activity of the VEGF was inhibited by 0.82 in the group treated with the high-concentration CSPG extract, and 0.84 in the group treated with the low-concentration. In this study, the CSPG extract was found to have a positive effect on the growth of hair length and an antioxidant effect, and suppress the activity of the VEGF, and thus it can be used as a candidate functional substance for the improvement of alopecia.
Machine learning has immense potential to diagnostic\nthe behavioral sciences, and may be especially useful with\nautism spectrum disorder. The Autism Diagnostic Interview-\nRevised (ADI-R) is a structured interview conducted with the\nparents of individuals who have been referred for the evaluation\nof possible autism or autism spectrum disorders. The degree of\ndisease (moderate, severe) is determined by the Childhood Autism\nRating Scale (CARS). The (CARS) is a behavior rating scale\nintended to help diagnose autism.In this paper, we introduced\na diagnose and determine the severity degree of autism using\nclassification to reduce the time and effort of physicians. Our\napproach designed in two phases are: single-label classification\nand Multi-label Classification. The first phase, applied singlelabel\nclassification technique with a synthetic minority oversampling\ntechnique (SMOT) to solve data imbalanced problem\nin our dataset. The second phase, Multi-label classification\napplied after concatenate the ADI-R and CARS datasets. The\nautism dataset collected from National Research Center in Egypt\n(NRC).The result of our approach that diagnose autism with 99.9\n% and the degree of autism with 95%.
Abstract- One of the most important assets in the manufacturing industry is the tooling used to manufacture the products. The tooling cost may be one of the highest cost in the manufacturing processes and, sometimes this cost it is not considered when the aggregated production plan is released, mainly due to the fact that the tooling must be available at any time. However, the production scheduling could be at risk if the tooling is not ready at the time required. Most of the production planning developed using linear programming (LP), just consider the tooling capacity but not the cost to prepare it, such as; set up, maintenance, spare parts and adjustments, etc. The problem considered in this paper is an analysis to include the tooling cost to solve an aggregated production planning with mathematical formulations of a mixed-integer LP model. Thus, this paper develops a mathematical model that interprets this problem and its treatment algorithm, focusing on aggregate production planning with multiple parts.